Estimation with Applications to Tracking and Navigation (Hardcover)

by Yaakov Bar-Shalom (Author), X. Rong Li (Author), Thiagalingam Kirubarajan (Author) "Estimation is the process of inferring the value of a quantity of interest from indirect, inaccurate and uncertain observations..." (more)
Key Phrases: Monte Carlo, Geometric Dilution of Precision, Selective Availability (more...)

Editorial Reviews

Product Description
Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation
Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics.
The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include:
* Problems that apply theoretical material to real-world applications
* In-depth coverage of the Interacting Multiple Model (IMM) estimator
* Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators
* Design guidelines for tracking filters
Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.

From the Back Cover
Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation

Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics.

The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include:

• Problems that apply theoretical material to real-world applications
• In-depth coverage of the Interacting Multiple Model (IMM) estimator
• Companion DynaEst™ software for MATLAB™ implementation of Kalman filters and IMM estimators
• Design guidelines for tracking filters

Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.

See all Editorial Reviews

Product Details

• Hardcover: 584 pages
• Publisher: Wiley-Interscience; 1 edition (June 8, 2001)
• Language: English
• ISBN-10: 047141655X
• ISBN-13: 978-0471416555
• Product Dimensions: 9.3 x 6.2 x 1.3 inches
• Shipping Weight: 2 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars See all reviews (2 customer reviews)
• Amazon.com Sales Rank: #238,145 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

17 of 17 people found the following review helpful:

5.0 out of 5 stars best standard book for target tracking system, May 8, 2001

By	Yong-Shik Kim (Pusan, south korea) - See all my reviews

This review is from: Estimation and Tracking:: Principles, Techniques, and Software (Ring-bound)

I think any person who major in target tracking system related to the Kalman filter must see this book. This book present the fundamentals of state estimation theory and the tools for the design of state-of-the-art algorithms for target tracking.

The book covers the basic concepts and estimation techniques for static and dynamic systems, linear and nonlinear, as well as adaptive estiomation. This constitutes a one semester graduate course in estimation theory in an electrical/systems engineering program.

The discussion deals mainly with discrete time estimation algorithms, which are natural for digital computer implementation. The basic state estimation algorithm-the Kalman filter-is presented in discrete as well as in continuous time. The use of the estimation algorithms is illustrated on kinematic motion models because they reveal all the major issues and in particular the subtleties encountered in estimation, and this serves as an introdution to tracking.

Guidelines for tracking filter design-selection of the filter design parameters-are given and illustrated in several examples.

At the end of each chapter, a number of problems that enhance the understanding of the theory and the connection of the theoretical material to the real world are given.

And I have this book as text for my paper.

3 of 3 people found the following review helpful:

5.0 out of 5 stars Excellent book on estimation/Kalman filter, September 28, 2004

By	S. Chow - See all my reviews (REAL NAME)

I don't usually write online reviews but this book is so clear and useful that I really want to recommend it to others. It is well written with a good outline and summary for every chapter. It also has a pretty diverse range of topics on estimation, including an introductory chapter on basic estimation approaches (e.g., ML, MAP, least squares), and very practical extensions (e.g., state augmentation, square-root filters). Even though I am not in EE and some of the examples are thus not particularly helpful to me, I still find this book one of the best of all the estimation/Kalman filter books out there.